Triple
T19012742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lensky – tenor |
E465267
|
entity |
| Predicate | emotionalColor |
P87208
|
FINISHED |
| Object | melancholic |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: melancholic | Statement: [Lensky – tenor, emotionalColor, melancholic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalColor Context triple: [Lensky – tenor, emotionalColor, melancholic]
-
A.
emotionalTrait
chosen
Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
-
B.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
-
C.
emotionalCounterpartOf
Indicates that one entity serves as the emotional equivalent, complement, or matching emotional role of another entity.
-
D.
emotionAssociation
Indicates an emotional relationship or connection that one entity has toward another entity or concept.
-
E.
emotionState
Indicates the emotional condition or feeling that an entity is currently experiencing.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a9bac8819093f9af57000667b0 |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.